R Notebook

library(tidyverse) 

Scenarios

True control concentration -> 4pg/ml
inter-cv -> 15 %
intra-cv -> 5 %

The ‘between’ plate SD will be Inter-CVxTrueMean/100 - QUANTITY WE WANT TO ESIMTATE/SET OUR LIMITS ON

true_mean <- 4  
inter_cv <- 15  
intra_cv <- 5  
between_plate_sd <- inter_cv*true_mean/100 
within_plate_sd <- intra_cv*true_mean/100



reps <- 10
plate_rep <- data.frame(rep_type = seq(1:reps), 
                        quad_i = rep()) 

Error in data.frame(rep_type = seq(1:reps), quad_i = rep()) : 
  arguments imply differing number of rows: 10, 0

plates <- 3
plate <- data.frame(plate = seq(1:plates), 
                    plate_i = rnorm(plates, true_mean, between_plate_sd))

plate

simulating_xmap_data <- function(plates_num = 3,
                                 reps_num = 8,
                                 true_mean = 4,
                                 inter_cv = 15,
                                 intra_cv = 5) {
  
  between_plate_sd <- inter_cv*true_mean / 100
  within_plate_sd <- intra_cv*true_mean / 100
  
  plates <- plates_num
  
  plate <- data.frame(
    plate = seq(1:plates),
    plate_i = rnorm(plates, true_mean, between_plate_sd)
  )
  
  reps <- reps_num
  plate_rep <- data.frame(rep_type = seq(1:reps))
  
  sim_plates <- tidyr::crossing(plate, plate_rep) %>%
    mutate(response = plate_i + rnorm(nrow(.), 0, within_plate_sd))
  
  
  sd_all <- sim_plates %>%
    summarise(sd = sd(response)) %>%
    pull()
  
  sd_plate <- sim_plates %>%
    group_by(plate) %>%
    summarise(mean = mean(response)) %>%
    summarise(sd = sd(mean)) %>%
    select(sd) %>%
    pull()
  
  vec <- data.frame(sd_all_reps = sd_all, sd_all_plates = sd_plate)
  return(vec)
  
}

Fix plates, vary reps

sim_over_plates <- imap_dfr(1:1000, ~ map_dfr(3:20, ~ 
                                                simulating_xmap_data(plates_num = .x), 
                                            .id = "plates"), 
         .id = "sim") %>% 
  mutate(plates = as.double(plates)) %>% 
  mutate(plates = plates + 3)

Fix reps, vary plates

Vary both plates and reps

params <- crossing(reps = seq(from = 4, to = 12, 
                              by = 2), 
                   plates = seq(from  = 3, to = 20, by = 2))

sim_param <- imap_dfr(1:1000, ~ params %>% 
  rowwise() %>% 
  summarise(results = simulating_xmap_data(plates_num = plates, 
                                           reps_num = reps)) %>% 
  unnest(cols = c(results)) %>% 
  bind_cols(params), 
  .id = "sim")